Utilizing RNA Sequencing Data for Genetic Insights and Drug Repurposing in Prostate Cancer

Prostate cancer (PC) is the second most common cancer and the fifth leading cause of cancer-related deaths among men as of ۲۰۲۰. Given the significant burden this disease places on healthcare systems, it is essential to explore better solutions. Since the development of new drugs requires substantial time and financial resources, drug repurposing, which reuses existing drugs to treat other diseases, has garnered considerable attention from scientists. Additionally, to gain deeper insights into the intracellular world and understand the biological and genetic mechanisms underlying diseases, enrichment analysis and the examination of differentially expressed genes (DEGs) can be highly beneficial. The use of RNA sequencing (RNA-Seq) data for PC—a next-generation, high-throughput sequencing technique—offers a powerful tool to help achieve these objectives. The GSE۲۹۱۵۵ dataset was downloaded from the GEO database, and RNA-Seq data from ۷ prostate cancer (PC) cell samples (LNCaP) and ۴ healthy epithelial cell samples (PrEC) as controls were obtained. Using the GEO۲R tool, the two groups were compared, and differentially expressed genes (DEGs) with a |log۲ fold change| > ۱ were selected. The upregulated and downregulated genes were then entered into the iLINCS database, and two approaches were followed: ۱. Perturbagens with a negative correlation and p-value < ۰.۰۵ were selected. A literature review was conducted, and the DrugBank platform was consulted to select FDA-approved drugs that had not been investigated or suggested in other studies. ۲. Gene ontology (GO) analysis was performed to examine molecular function (MF), cellular components (CC), and biological processes (BP). Additionally, KEGG and STRING were used to identify the key pathways and draw the protein-protein interaction (PPI) network, from which the hub proteins were obtained using Enrichr. After conducting the analyses, ۲,۹۳۵ down-regulated genes and ۲,۹۸۳ up-regulated genes were identified. From the ۳,۰۸۹ drugs suggested by iLINCS, Pitavastatin and Perampanel were selected as final drugs. Enrichment analyses in Molecular Function (MF), Cellular Component (CC), and Biological Process (BP) categories revealed Cadherin Binding, Focal Adhesion, and Regulation of Cell Migration, respectively. Additionally, the key pathway of Axon Guidance was identified. Based on the highest p-values, ۱۰ hub proteins were identified, and a Protein-Protein Interaction (PPI) network was drawn. Pitavastatin, an HMG-CoA reductase inhibitor commonly used to reduce cardiovascular disease risk, has been studied for its anti-cancer mechanisms in various cancers. Similarly, Perampanel, an antagonist of glutamate and aspartate receptors (AMPAR and NMDAR), is typically used as an anticonvulsant but has shown anticancer effects in brain cancers and neuroendocrine tumors such as small cell lung cancer. Given these properties, we can anticipate its potential efficacy in PC, particularly in the aggressive neuroendocrine subtype of prostate cancer (NEPC). The enrichment analyses collectively highlighted cell migration and adhesion processes, where the disruption of gene expression balance plays a critical role in promoting tumor progression, including metastasis. These findings hold significant promise for developing targeted therapies and improving diagnostic strategies in PC. In the end, further in vitro and in vivo studies are recommended to validate these results.

کلیدواژه ها:

prostate cancer ، drug repurposing ، RNA sequencing